Da (3).mp4 May 2026

# Load a pre-trained model model = torchvision.models.resnet50(pretrained=True) model.eval() # Set to evaluation mode

# Move to GPU if available device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') tensor_frame = tensor_frame.to(device) model.to(device) da (3).mp4

# Process features as needed print(features.shape) # Load a pre-trained model model = torchvision

# Add batch dimension tensor_frame = tensor_frame.unsqueeze(0) da (3).mp4

# Transform to apply to frames transform = transforms.Compose([ transforms.ToTensor(), transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]) ])